# Copyright (c) 2024 Intel Corporation
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#      http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

from nncf.common.graph.model_transformer import ModelTransformer
from nncf.common.graph.transformations.commands import TransformationType
from nncf.experimental.tensorflow.graph.transformations.layout import TFTransformationLayoutV2
from nncf.experimental.tensorflow.nncf_network import NNCFNetwork


class TFModelTransformerV2(ModelTransformer):
    """
    Applies transformations to the NNCF network.

    The `TFModelTransformerV2` does not modify the model config to insert
    compression operations to the model. The `TFModelTransformerV2` adds
    pre-hook or post-hook to the wrapped TF operation instead of that.
    In this way, compression operation falls into the model.
    """

    def __init__(self, model: NNCFNetwork):
        """
        Initializes the model transformer.

        :param model: NNCF network.
        """
        super().__init__(model)

    def transform(self, transformation_layout: TFTransformationLayoutV2) -> NNCFNetwork:
        """
        Applies transformations to the model.

        :param transformation_layout: An instance of `TransformationLayout` that
            includes a list of transformations to be applied to the NNCF network.
        :return: The transformed NNCF network.
        """
        for command in transformation_layout.transformations:
            if command.type == TransformationType.INSERT:
                self._model.insert_at_point(command.target_point, command.insertion_objects)
            elif command.type == TransformationType.REMOVE:
                # TODO(andrey-churkin): Add support
                pass
            else:
                raise ValueError(f"Transformation type {command.type} does not support.")

        return self._model
